Tamoxifen induces stem-like phenotypes and multidrug resistance by altering epigenetic regulators in ERα+ breast cancer cells

Kalyanaraman, Aparna; Gnanasampanthapandian, Dhanavathy; Shanmughan, Prasad; Kishore, Puneet; Ramalingam, Satish; Arunachalam, Rathnaswami; Jayaraman, Selvaraj; Kaliappan, Ilango; Munuswamy-Ramanujam, Ganesh; Ilangovan, R.; Sambandam, Yuvaraj; Anbalagan, Muralidharan; Chandrakesan, Parthasarathy; Palaniyandi, Kanagaraj

doi:10.21037/sci-2020-020

Cited by 5 publications

(3 citation statements)

References 37 publications

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“…The tumour formation at the secondary site reflects the stemness potential of cancer cells, which can be tracked via detecting the colony-forming potential ( Sharma et al, 2022 ). The exposure of tamoxifen in MCF-7 cells resistant to tamoxifen (MCF7-TR) resulted in an increased number of CSCs as observed by the increased number of ALDH+ cells accompanied by increased colony formation, a higher number of mammospheres, and alterations in epigenetic and multidrug resistance (MDR) stem cell marker genes ( Kalyanaraman et al, 2020 ). In addition, radioresistant breast cancer cells (RT-R-MDA-MB-231) showed increased colony formation and expression of CD44 and other markers of CSCs such as Notch, ALDH1, or OCT3/4 ( Ko et al, 2018 ).…”

Section: Breast Cancer Stem Cells (Bcscs)mentioning

confidence: 99%

Therapy-resistant breast cancer in focus: Clinically relevant mitigation by flavonoids targeting cancer stem cells

et al. 2023

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Significant limitations of the reactive medical approach in breast cancer management are clearly reflected by alarming statistics recorded worldwide. According to the WHO updates, breast malignancies become the leading cancer type. Further, the portion of premenopausal breast cancer cases is permanently increasing and demonstrates particularly aggressive patterns and poor outcomes exemplified by young patients with triple-negative breast cancer that lacks targeted therapy. Accumulating studies suggest the crucial role of stem cells in tumour biology, high metastatic activity, and therapy resistance of aggressive breast cancer. Therefore, targeting breast cancer stem cells is a promising treatment approach in secondary and tertiary breast cancer care. To this end, naturally occurring substances demonstrate high potential to target cancer stem cells which, however, require in-depth analysis to identify effective anti-cancer agents for cost-effective breast cancer management. The current article highlights the properties of flavonoids particularly relevant for targeting breast cancer stem cells to mitigate therapy resistance. The proposed approach is conformed with the principles of 3P medicine by applying predictive diagnostics, patient stratification and treatments tailored to the individualised patient profile. Expected impacts are very high, namely, to overcome limitations of reactive medical services improving individual outcomes and the healthcare economy in breast cancer management. Relevant clinical applications are exemplified in the paper.

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Section: Breast Cancer Stem Cells (Bcscs)mentioning

confidence: 99%

Therapy-resistant breast cancer in focus: Clinically relevant mitigation by flavonoids targeting cancer stem cells

et al. 2023

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“…Breast cancer (BC) has one of the highest rates of cancer deaths among women worldwide, with long-term exposure to estrogen considered to be the principal factor leading to its tumorigenesis; estrogen-dependent BC accounts for approximately 2/3 of BC cases ( 1 , 2 ). In addition, clinical research using anti-estrogens or aromatase inhibitors to reduce local and distant recurrence has revealed that estrogen promotes the development of BC ( 3 ).…”

Section: Introductionmentioning

confidence: 99%

ERα promotes SUMO1 transcription by binding with the ERE and enhances SUMO1-mediated protein SUMOylation in breast cancer

Wang¹,

Zhang²,

Yang³

et al. 2023

Gland Surg

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Background Estrogen plays a crucial role in the tumorigenesis of breast cancer (BC), and epigenetic modification by SUMOylation is essential for cancer development. However, the mechanism underlying estrogen’s actions on protein SUMOylation and its effect on BC development are still incompletely understood. Methods SUMO1 in BC cell lines was verified via real-time quantitative PCR (RT-qPCR) and western blot. Cell proliferation and colony formation assays was also performed to evaluate SUMOylation as mediated by SUMO1 . Luciferase activity to examine whether E2 promoted the transcription of SUMO1 , and chromatin immunoprecipitation (ChIP) assay to determine the binding of estrogen receptor alpha (ERα) to SUMO1 were conduction, and an animal model was used to evaluate the effects of E2-ERα-enhanced SUMO1 transcription. Results E2 promoted SUMO1 mRNA and protein expression levels in a dose- and time-dependent manner in ER-positive BC cells; it exerted no influence on SUMO2/3 expression; in E2-induced SUMO1 transcription, ERα, but not ERβ, was essential to the process. In addition, E2-ERα upregulated the transcription of SUMO1 by binding with an estrogen-response element half-site (1/2ERE, in the −134 to −123 bp region) of the SUMO1 promoter, and E2-ERα induced SUMO1 transcription-enhanced cellular viability in ER-positive BC cells. To further determine SUMOylation as mediated by SUMO1 in ER-positive BC, we evaluated novel SUMO1 target proteins such as Ras and demonstrated that E2 increased Ras SUMOylation and cellular proliferation by affecting downstream signaling-pathway transduction. Finally, our data revealed that E2-ERα enhanced SUMO1 transcription to promote tumor growth in a BC orthotopic tumor model. Conclusions Collectively, our results showed that E2 promoted the transcription and protein expression of SUMO1 via ERα binding to a 1/2ERE in the SUMO1 promoter, and that E2-ERα also augmented SUMO1-mediated Ras SUMOylation and mediated cellular responses in ER-positive BC. We therefore achieved significant insights into the mechanism involved in ER-positive BC development and provided a novel target for its treatment.

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“…Under the current level of medical care, the 5-year survival rate of breast cancer patients can reach more than 89 %. Such good therapeutic effect of breast cancer is mainly attributed to the emergence of a large number of estrogen receptor (ERα) antagonist drugs in recent years, such as tamoxifen and raloxifene [3], the most commonly used drugs in the clinical treatment of breast cancer.…”

Section: Introductionmentioning

confidence: 99%

Application of machine learning algorithms in drug screening

Jin,

Rong,

Chang

2023

J., complex., health sci.

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At present, in the medical field, drug screening is usually performed using in vivo drug experiments. However, it is very time-consuming and laborious to conduct in vivo experiments on a large number of drugs to be screened one by one. This paper attempts to propose using machine learning algorithms to perform preliminary screening of a large number of compounds to be screened and their molecular structures to reduce the workload of in vivo experiments. Among them, it is internationally recognized that there is an important association between breast cancer progression and the alpha subtype of the estrogen receptor. Anti-breast cancer drug candidates with excellent efficacy need to contain compounds that can better antagonize ERα activity. In this paper, the research object is narrowed down from compounds to the molecular structure of the compounds, and then the random forest regression algorithm is used to develop the molecular structure-ERα activity prediction model. Molecular structures with significant effects on biological activity were screened from molecular structure descriptors in numerous compounds. Four different kernel functions were used to conduct comparative experiments, and finally a support vector regression algorithm based on radial basis kernel function was established, which realized the quantitative prediction of compounds on biological activity of ERα, and could find potential compounds beneficial to breast cancer treatment. This is a novel, computer-based method for preliminary drug screening, which can help medical researchers effectively narrow the scope of experiments and achieve more accurate optimization of drugs.

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Tamoxifen induces stem-like phenotypes and multidrug resistance by altering epigenetic regulators in ERα+ breast cancer cells

Cited by 5 publications

References 37 publications

Therapy-resistant breast cancer in focus: Clinically relevant mitigation by flavonoids targeting cancer stem cells

Therapy-resistant breast cancer in focus: Clinically relevant mitigation by flavonoids targeting cancer stem cells

ERα promotes SUMO1 transcription by binding with the ERE and enhances SUMO1-mediated protein SUMOylation in breast cancer

Application of machine learning algorithms in drug screening

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